DEVELOPMENT... OpenML
Run
12738

Run 12738

Task 22 (Supervised Classification) mfeat-zernike Uploaded 22-05-2014 by Felicia West
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Flow

weka.SMO_RBFKernel(1)J. Platt: Fast Training of Support Vector Machines using Sequential Minimal Optimization. In B. Schoelkopf and C. Burges and A. Smola, editors, Advances in Kernel Methods - Support Vector Learning, 1998. S.S. Keerthi, S.K. Shevade, C. Bhattacharyya, K.R.K. Murthy (2001). Improvements to Platt's SMO Algorithm for SVM Classifier Design. Neural Computation. 13(3):637-649. Trevor Hastie, Robert Tibshirani: Classification by Pairwise Coupling. In: Advances in Neural Information Processing Systems, 1998.
weka.RBFKernel(1)_C250007
weka.RBFKernel(1)_G100.0
weka.SMO_RBFKernel(1)_C100.0
weka.SMO_RBFKernel(1)_Kweka.classifiers.functions.supportVector.RBFKernel
weka.SMO_RBFKernel(1)_L0.001
weka.SMO_RBFKernel(1)_N0
weka.SMO_RBFKernel(1)_P1.0E-12
weka.SMO_RBFKernel(1)_V-1
weka.SMO_RBFKernel(1)_W1

Result files

xml
Description

XML file describing the run, including user-defined evaluation measures.

arff
Predictions

ARFF file with instance-level predictions generated by the model.

19 Evaluation measures

Area under ROC curve
0.5138
Per class
F measure
0.0721
Per class
Kappa
0.0167
KB relative information score
164.2623
Mean absolute error
0.1799
Mean prior absolute error
0.18
Number of instances
2000
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.4527
Per class
Predictive accuracy
0.115
Prior entropy
3.3219
Recall
0.115
Per class
Relative absolute error
0.9995
Root mean prior squared error
0.3
Root mean squared error
0.3063
Root relative squared error
1.0209
SciMark benchmark
948.4836[562.11430287262971015.7907504114269483.88543266528814911.48820099582031769.1393263693276]

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